Prognostic factors associated with changes in knee pain outcomes, identified from initial primary care consultation data. A systematic literature review

Abstract Background Data collected during initial primary care consultations could be a source of baseline prognostic factors associated with changes in outcome measures for patients with knee pain. Objectives To identify, appraise and synthesize studies investigating prognostic factors associated with changes in outcome for people presenting with knee pain in primary care. Methods EMBASE, CINAHL, AMED, MEDLINE and MedRxiv electronic databases were searched from inception to March 2021 and repeated in August 2022. Prospective cohort studies of adult participants with musculoskeletal knee pain assessing the association between putative prognostic factors and outcomes in primary care were included. The Quality in Prognostic Studies (QUIPS) tool and The Modified Grading of Recommendations Assessment, Development and Evaluation (GRADE) framework, specific to prognostic reviews were used to appraise and synthesize the evidence respectively. Results Eight studies were included. Eight knee pain outcomes were identified. Methodological and statistical heterogeneity resulted in qualitative analysis. All evidence was judged to be of low to very low quality. Bilateral knee pain (multivariable odds ratio (OR) range 2.60–2.74; 95%CI range 0.90–8.10, p value = 0.09) and a lower educational level (multivariable (OR) range 1.74–5.6; 95%CI range 1.16–16.20, p value = <0.001) were synonymously associated with persisting knee pain at 12-month follow up. A total of 37 univariable and 63 multivariable prognostic factors were statistically associated with outcomes (p ≤ 0.05) in single studies. Conclusions There was consensus from two independent studies that bilateral knee pain and lower educational level were associated with persistent knee pain. Many baseline factors were associated with outcome in individual studies but not consistently between studies. The current understanding, accuracy and reliability of the prognostic value of initial primary care consultation data for knee pain outcomes are limited. This review will provide an essential guide for candidate variable selection in future primary care prognostic confirmatory studies. Key messages Bilateral knee pain and lower educational level were associated with persistent knee pain. Many baseline factors were associated with outcome in individual studies but not consistently between studies. The current understanding, accuracy and reliability of the prognostic value of initial primary care consultation data for knee pain outcomes are limited.


Introduction
Musculoskeletal (MSK) pain is a leading cause of disability worldwide and is likely to rise globally with an ever-growing population and increased life expectancy [1,2]. MSK pain accounts for 22% of the total burden of ill health in the UK [3]. Knee pain is one of the most common complaints observed, with prevalence rates in the general population estimated to be between 19 and 35% [4,5].
People suffering from knee pain are frequently managed in primary care and represent approximately 10% of all primary care consultations for MSK conditions [6]. For the purposes of this review, primary care refers to services provided by registered medical or healthcare practitioners (generally in community settings), which provide patients with an initial point of contact or consultation where they can seek advice or assessment of a health complaint or condition. Examples include general practitioners, paramedic practitioners, physician associates, first contact physiotherapy practitioners and nurse practitioners.
During initial consultations, practitioners typically conduct a detailed review of the history of the current condition and perform a clinical assessment to establish a working diagnosis. Current primary care management models recommend an array of further diagnostic investigations or management options; this can include advice, physiotherapy, pharmacological management or onward specialist referral (i.e. transfer to secondary care) [7][8][9]. However, selecting the most appropriate course of action can be challenging and clinical decisions are usually influenced by, and can be biased towards, a practitioner's scientific knowledge and skillset [10].
To assist practitioners, evidence can be considered from prognostic factor research [11]. Prognostic factors are any measurements, characteristics or variables (such as routine data collected during initial consultations, for example) that are associated with a change in risk or probability of the occurrence of a future health-related outcome among patients with a defined health condition [12][13][14][15][16]. Variation in the values, levels or categories of individual factors will result in risk or probability differences for the occurrence of health outcomes between patients [11]. This means that prognostic factors are useful to explain why some patients have a better or worse prognosis than others [14]. Furthermore, identification of prognostic factors can inform treatment recommendations and help facilitate development of innovative treatment approaches if there is evidence of a causal link between the factor and outcome [14].
Multiple prognostic factors can also be used in combination to develop clinical prediction models, providing patients with individualized estimates of risk or probability of a future health outcome at the point of consultation [17]. Prognostic models can also facilitate stratified management, where bespoke clinical management decisions can be informed by an individual's risk or probability estimate and profile of prognostic factors [16]. Therefore, if robust prognostic factors for the likely course of knee pain could be identified at initial consultation, this may improve the effectiveness and efficiency of various clinical decisions, thus benefitting patients and health care providers alike.
Previous studies conducted in secondary care settings (i.e. acute hospitals) have identified a number of prognostic factors associated with worsening knee pain outcomes in adults, including increasing age and body mass, as well as a history of sustaining a previous knee injury [18,19]. Several generic prognostic factors for MSK conditions have been established in the primary care setting such as pain intensity, widespread pain, high functional disability, somatization and movement restriction [20]. However, there is currently limited evidence related to prognostic factors associated with changes in health outcomes for people specifically suffering from knee pain.
Consequently, because of the burden of knee pain on primary care services and the potential benefits of utilizing prognostic factors in practice, there is a clear need to explore whether routine data obtained at the point of initial consultation has prognostic value. Therefore, the aim of this systematic review is to summarize, appraise and synthesize the evidence to identify prognostic factors associated with changes in knee pain outcome in adult patients, obtained from data derived from initial primary care consultations. This, to the best of our knowledge, has not been conducted previously.

Methods
Our methodology was specified a priori and registered with the International Prospective Register of Systematic Reviews (PROSPERO) registration ID; CRD42021229699. This review was reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines [20]. Ethical approval and consent was not required in the absence of human participants.

Data sources and search strategy
The EMBASE, CINAHL, AMED, MEDLINE and MedRxiv electronic databases were searched from inception to March 2021 and repeated in August 2022. The search strategy is presented in supplementary files 1-4. Searches were limited to original research articles published in the English language. Systematic reviews, editorials and conference abstracts were excluded. A hand search from all included articles was also undertaken to avoid omitting potentially relevant articles.

Participants
Studies were included if participants: (1) were adults aged 18 years or over; (2) sought an initial primary care consultation with a registered health care or medical professional for MSK knee pain of any duration; (3) had not received any prior management. Studies were excluded if participants: (1) underwent surgery or enrolled in postoperative knee rehabilitation; (2) had non-MSK knee pain (e.g. malignancy); (3) had referred pain from other sources (e.g. radiculopathy); (4) had systemic inflammatory conditions with associated knee pain (i.e. that manifested as monoarticular or polyarticular inflammatory arthropathies; (5) had a subluxation, dislocation or fracture/s; (6) had a serious lumbar pathology; (7) had been referred to secondary care management.
Study design. Studies were included if they: (1) were a prospective or retrospective cohort, case-control or nested case-control design; (2) specifically investigated the association between candidate prognostic factors, measured within 2 weeks of the initial primary care consultation date and outcome measures relevant to knee pain; (3) conducted multivariable analyses to adjust for the prognostic effect of other important candidate prognostic factors, such as age and biological sex. Studies were excluded if they: (1) were of any other design (N ¼ 4) or; (2) were not exclusively primary care based (N ¼ 29) or; (3) surgery used as an intervention (N ¼ 7).
Prognostic factors. Studies were included if any of the following data (obtained from initial consultations) were investigated as candidate prognostic factors: (1) patient characteristics; (2) demographics; (3) recreational activities; (4) radiographic imaging; (5) blood tests; (6) knee symptoms; (7) clinical examination; (8) general health; (9) clinical or radiographic findings that are reported within 2 weeks from initial consultation. Additionally, if there was evidence of the conduct of multivariable analyses to adjust for the prognostic effects of other important prognostic factors, including age and biological sex.
Outcome measures. Studies were included if they investigated specific outcome measures for knee pain, in the domains of pain, function, disability, general health and quality of life scores.

Study selection
Studies were initially screened using the title and abstract for potential full-text review by the primary author (TC). All potentially eligible full-text studies were jointly reviewed in an independent blinded manner by the primary (TC) and secondary author (TH) against all pre-defined eligibility criteria. Disagreements were resolved by discussion between the primary and secondary authors until mutual agreement was reached, no arbitration was required.

Data extraction
Data were extracted by one reviewer (TC) according to the Checklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies -Prognostic Factors [11] (Supplementary file 5). Extracted data were checked for consistency by all reviewers in an unblinded manner.

Risk of bias
Risk of bias (RoB) was assessed for all included studies using The Quality in Prognostic Studies (QUIPS) tool, by two reviewers (TC, TH) in an independent blinded manner. The QUIPS tool is a reliable method of RoB evaluation for studies of prognostic factors through six independent domains, which include: (1) study participation; (2) study attrition; (3) prognostic factor measurement; (4) outcome measurement; (5) study confounding; (6) statistical analysis and reporting [21]. Studies were classified as low, moderate, or high RoB based on the QUIPS tool guidance for ROB judgements (see Supplementary file 6) [21,22]. Any disagreements were resolved through discussions. A third reviewer, acting as an arbitrator, was not required.

Data analysis and synthesis
Extracted data and QUIPS appraisals were tabulated for each included study to facilitate the evidence synthesis and assess study heterogeneity (Table 1). Data synthesis was conducted according to the modified Grading of Recommendations Assessment, Development and Evaluation (GRADE) framework to assess and grade the quality of evidence [23]. All statistically significant prognostic factors that were investigated by single studies or those that were investigated by two or more studies were tabulated and grouped according to each knee outcome (Table 2). Where homogenous effect measures were reported for the same prognostic factor across two or more studies, these were summarized using forest plots (Figures 2 and 3). Key judgements for each prognostic factor in the following modified GRADE domains were made: (1) study limitations; (2) consistency of results; (3) effect sizes; (4) precision of results; (5) publication bias; and (6)  prognostic value were made when considering effect size, subjective interpretation of 95% confidence interval (CI) width and p value size. Effect estimates were deemed to be of potential significant prognostic value if there was evidence of a moderate effect size (in the absence of excessively wide CIs) or small effect size (with narrow CIs) and were displayed in bold text and underlined (

Study selection
The searches returned 123 results with 11 duplicates, leaving 112 studies. After screening titles and abstracts, 97 were excluded. The remaining 15 studies underwent full-text evaluation, where a further seven were excluded. Eight studies were included within the evidence synthesis ( Figure 1). All excluded studies are listed, with reasons for exclusion in Supplementary file 9.

Characteristics and quality of included studies
For all included studies, the characteristics, candidate prognostic factors, outcomes and QUIPS assessments are presented in Table 1. A narrative summary of these elements across studies is provided below.

Sample size
None of the included studies specified a sample size calculation or justified the sample size used.
Psychosocial factors were investigated in all eight studies, although some specific factors were reported in only one study. Education level was the most frequent reported factor [24][25][26]28,31]. Three studies investigated coping strategies with pain [24,31] and fear of movement [31] using the six subscales from the pain coping inventory (PCI) and the Tampa Scale for Kinesiophobia respectively. Two studies recorded anxiety [29,30] and two studies recorded sick leave as candidate variables [26,27].
Candidate factors derived from radiological and haematological investigations were infrequent. Two studies used X-ray investigations [24,30], one assessed both the knee and hip [24] and one assessed the knee only [30]. One study included blood markers, specifically erythrocyte sedimentation rate as a potential prognostic factor [22].

Outcomes
Knee pain outcome measures were reported by two studies [24,31]; 10 and 11 point numerical rating scales (NRS) were used, respectively. Two studies investigated persistent knee symptoms, using several standardized self-reported symptom questionnaires where responses were dichotomized [25,27]. Belo et al. [25] used the WOMAC, the Medical Outcomes Study Short Form 36 Health Survey (SF-36), the Knee Society Score (KSS) function questions, the Lysholm Knee Scoring Scale, the Tampa Scale for Kinesophobia (assessed at baseline) and questions about experience of recovery or worsening. Kastelein et al. [27] used the Knee Society Score, the Lysholm Knee Scoring Scale and the WOMAC.
One study utilized an unfavourable knee outcome, defined as the presence of persistent knee symptoms or having undergone knee replacement surgery during a six year follow up [26]. Two studies assessed selfreported perceived knee recovery [28,31]; one used an ordinal scale that was dichotomized according to whether clinical recovery occurred or not [31]. The other also categorized perceived clinical recovery (completely recovered and much improved versus persistent knee symptoms (slightly improved, no change, slightly worsened, much worsened and worse than ever) [28]. Three studies assessed functional outcomes, Figure 3. Graph comparing bilateral knee symptoms as a prognostic factor for persisting knee symptoms in two at 12-month follow upodds ratio analyses.

Risk of bias within and across studies
General The overall quality of reporting across studies was variable. Out of 48 domains that were reported across all studies, 11 domains (23%) were classed as having low RoB. Most domains across studies were classed as moderate (20 domains or 42%) or high RoB (17 domains or 35%) ( Table 1).

Participation
Five studies were classed as low [24][25][26][27][29][30][31] and three of moderate RoB [26][27][28] in terms of participation reporting. Three did not provide dates of the study recruitment period [26][27][28]. Those considered low RoB reported on recruitment periods, geographical location and characteristics of the study population. Studies considered of moderate RoB demonstrated variable reporting quality. Key characteristics of the population source and recruitment periods were unclear but other key information such as recruitment place and eligibility criteria were specifically stated for all included studies.

Study attrition
Four studies were considered as high RoB as key characteristics of loss and rate of loss to follow-up were either not described or ambiguously reported [26,[29][30][31]. One was considered of moderate risk due to ambiguous reporting of attrition and key characteristics [27]. Three were considered of low risk; there was low attrition rates and specific details provided for loss to follow up, key characteristics of those lost [24,25,28].

Prognostic factors
Five studies were considered of moderate RoB [25,26,[29][30][31]. Reliability and validity of prognostic factor measurement methods were not reported; the method of imputation for missing prognostic factor data was also not reported in three studies [29][30][31].
For candidate factors that consisted of continuous data, the type of variable categorization was not specifically stated in four studies [26,[29][30][31].
The remaining studies were considered high RoB; they did not report missing data, state definitions for categorical data or the reliability of prognostic factor measurement [24,27,28].

Outcome measurement
No studies were considered of high RoB with respect to outcome. Four were considered of moderate risk because they did not report validity and/or reliability for outcome measures, a potential source of misclassification bias according to QUIPS criteria [24,25,27,28,31]. The remaining studies were considered low risk with follow up time frames were clearly defined [24,26,29,30]. Two of which described the validity of the outcome measure but did not describe its reliability [29,30].

Adjustment for other prognostic factors
We pre-specified that as a minimum, studies should adjust for age and biological sex in their multivariable analyses as these were common to all participants in all studies. Four studies adjusted for the prognostic effect of both, and were considered as moderate RoB [24,26,27,31]. The remaining four studies were considered high RoB because only age was adjusted for but not biological sex [24,26,29,30] and definitions for other prognostic factors used for adjustment were either unclear or not reported [24,26,29,30]. Additionally, handling of missing data was not reported in three of these four studies [24,29,30].

Statistical analysis
All included studies used univariable screening to select prognostic factors for inclusion in multivariable models based upon statistical significance. This datadriven approach to prognostic factor selection is generally not recommended for constructing multivariable models, as it may result in some clinically important factors being excluded from final analyses; this means that prognostic effects may not be properly adjusted for. Instead, recent recommendations are that multivariable models should be constructed using prognostic factors identified from the literature and clinical reasoning [10,33]. Therefore, none of the included studies could be considered as low RoB. Five studies were considered high risk, because there was evidence of selective reporting [24,26,[29][30][31]. Only one had a study protocol to make a direct comparison between proposed outcomes and those reported in the full-text publication [26]. Therefore, outcomes listed in the methods section of the remaining studies were compared with those reported in the results section. Although outcomes reported in results were consistent with outcomes specified in methods in all five studies, there was inadequate reporting of non-significant prognostic indicators in the results.

Data synthesis
Unfortunately, due to the observed heterogeneity in terms of study methodology, prognostic factors, prognostic effect measures and the large proportion of domains classed as moderate to high RoB, a meta-analysis could not be performed. Instead, a narrative synthesis is presented below. A summary of all significant and insignificant prognostic factors derived from all studies (with their associated effect measures, CIs and p values) are listed in Table 2 and Supplementary file 10, respectively. Prognostic factors derived from single studies, or factors that were investigated by more than one study are grouped according to the specific outcome measures investigated.

Results of studies
Across all studies and follow up time points, a total of 74 prognostic factors were identified ( Table 2). A total of 38 and 63 statistically significant univariable and multivariable prognostic factors were identified, respectively. All evidence was considered to be of low to very low quality according to GRADE criteria [23]. This was due to phase 1 explanatory cohort designs, and almost all prognostic factors were established from single studies. This limited between study comparisons in terms of effect sizes, precision, consistency of results and publication bias.

Knee pain
Thirteen statistically significant prognostic factors were identified from one low to very low-quality graded study (Table 2). Eight prognostic factors were related to short-term follow up (3 months), and five related to medium term (12 months) follow up [31]. Eleven were associated with small to moderate effect sizes with narrow and wide CIs respectively which may have prognostic value (Table 2). Statistically significant univariable prognostic associations are unknown because this was not reported, only that univariable factors met a predefined level of significance (p < 0.20) to be considered for multivariable analysis.
A history of non-traumatic knee symptoms was also identified as a prognostic factor in two studies [9,14] [27].
At 18 months, there were 15 statistically significant prognostic factors consistent in both univariable and multivariable analysis derived from two studies that were associated with outcome with narrow CIs [29,30]. Finally, while the presence of bilateral knee pain (RR 1.28 95%CI ¼ 0.98-1.68 p ¼ 0.068) and morning stiffness lasting >30 min (RR 1.55 95%CI ¼ 0.99-2.43 p ¼ 0.057) were classed as non-significant in multivariable analysis (Supplementary file 10), they may still have some limited prognostic importance due to moderate effect sizes [28].

Discussion
This review has summarized, appraised and synthesized the evidence to identify prognostic factors associated with changes in outcomes relevant to knee pain in adult patients, using data obtained from initial primary care consultations.
All evidence included in this review was low or very low quality according to the modified GRADE assessment (Table 2). This could be explained in part because all included studies were described as phase 1 prognostic studies, i.e. studies that have exclusively sought to identify and explore any potential associations between outcomes and candidate prognostic factors [34]. Consequently, when using the modified GRADE criteria, a moderate quality of evidence was the maximum score that could be obtained. Studies were then downgraded if there was evidence of imprecision (including absence of sample size calculation) and inconsistency of results, where associations have not been confirmed in other studies [23]. In particular, between-study heterogeneity limited the number of comparisons that could be made in terms of effect measures, follow up time points, candidate prognostic factors and outcome measures. It is clear that further research is required to provide evidence of the consistency of these results across other cohorts. A significant issue identified was related to the general conduct of multivariable analyses. To establish the independent association of a prognostic factor and an outcome, analyses should be adjusted for other important prognostic factors that may otherwise distort the true relationship [14,16]. It has been suggested that age [19,35,36] and biological sex [37][38][39] have previously been shown to be associated with worsening knee outcomes. Consequently, we stated a priori (PROSPERO) registration ID; CRD42021229699) that these should be essential factors used for adjustment purposes, as these are common to all participants and thus may have an influence on prognostic estimates through mechanisms such as confounding, mediation and moderation [11]. However, only four studies adjusted for both the prognostic effects of age and biological sex [25][26][27]31]. Instead, univariable screening was commonly used to select candidate prognostic factors for inclusion in multivariable models, based upon statistical significance [10,17]. While this may have been acceptable practice previously, it is unlikely that models were adjusted appropriately using other clinically important prognostic factors. Indeed, current recommendations suggest that candidate factors should be selected for inclusion based upon existing evidence and clinical reasoning, to ensure all important factors are considered [17]. Several included papers [24,26,[29][30][31] were appraised as low or very low quality using QUIPS.
Whilst we acknowledge that these papers might have been considered as high quality at the time of publication, the introduction and advancement of reporting guidelines (such as the Reporting recommendations for tumour MARKer prognostic studies [40] and appraisal guidelines (such as QUIPS) in response to evolving best practice means that unfortunately, these papers inevitably fall short of current required standards. Importantly though, these papers have provided an essential foundation to underpin advancements in primary care prognostic research.
Despite the low quality of graded evidence, there was consensus from two studies that a lower education level and bilateral knee symptoms were independently associated with an increased odds of persistent knee pain at 12-month follow up [25,27]. This has potential clinical importance for healthcare practitioners working in a primary care setting because patients who present with bilateral knee pain that have a lower educational background at initial consultation may have greater odds of longer-term symptoms. However, it must be remembered that because of the low overall quality of the evidence, the prognostic value of these factors should only be considered provisional to be confirmed in future studies. Despite their relatively limited clinical value, in terms of further prognosis research, these prognostic factors would be suitable for inclusion in any future studies to develop a prognostic model to predict changes in knee pain over time.
Our results are consistent with other similar reviews of generic prognostic factors MSK outcomes in primary care [20] and prognostic factors for the shoulder joint in secondary care [41] which have both suggested caution in their conclusions due to selective reporting, poor control of confounding, bias in study design and small sample sizes within primary studies. We found that some of the potential prognostic factors identified from low-quality studies were consistent with those observed for changes in knee pain outcomes in secondary care [18,19]. Specifically, these factors (Table 2) include increased age [26,29], increased body mass [22,26,27,29] and previous knee injury [24,29]. We also found that some prognostic factors identified from single, low-quality studies were also consistent with prognostic factors for generic MSK pain outcomes observed in primary care [32]. These factors ( Table 2) that may have importance include higher pain severity at baseline [31], longer pain duration [31], multiple-site pain [24,26], anxiety and/or depression [29,31], adverse coping strategies [31] and older age [26,29]. Nevertheless, because of the similar issues afflicting the quality of the wider evidence base, any consistency between our findings and these studies should be interpreted with caution. There is a need for a greater number of well-conducted studies to further our understanding related to prognostic factors and their relationship with knee pain in both primary and secondary care settings.
Finally, we found that six of the eight included studies were based in the Netherlands [25][26][27][28]31]. The south of the Netherlands is particularly prone to significant land rise [42] and previously, a mountainous landscape was found to be an independent prognostic factor for knee pain [43]. How generalizable the current review findings are to other nationalities with flatter gradients is uncertain. Further high-quality exploratory and confirmatory prognostic factor studies are required that utilize large cohorts of primary care patients based in other countries.

Limitations
Our review only considered peer-reviewed published studies and pre-prints from the MedRxiv database. An extensive search of conference abstracts and other grey literature was not conducted, which may have inadvertently introduced some publication bias [44,45].
The QUIPS appraisal tool was used as it is specific to prognostic research for systematic reviews and has been demonstrated to have high reliability [21]. However, we did not formally establish inter-rater reliability between reviewers.

Conclusion
This is the first systematic review that has investigated candidate prognostic factors identified from data collected at initial primary care consultation, and associations with changes in outcomes for patients with knee pain. Results from two papers suggest that the presence of bilateral knee pain and a lower educational level were independently associated with persisting knee pain at 12-month follow up. However, this must be interpreted with caution because results obtained are derived from a pool of low to very low quality of evidence. Other factors were identified as having potential associations with various knee pain outcome measures, but all were derived from single studies. Further research is essential to improve the knowledge base of this important area of primary care MSK research [46].